Path Loss Exponent Estimation for Wireless Sensor Network Localization
Date
2007
Authors
Mao, Guoqiang
Anderson, Brian
Fidan, Baris
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Elsevier
Abstract
The wireless received signal strength (RSS) based localization techniques have attracted significant research interest for their simplicity. The RSS based localization techniques can be divided into two categories: the distance estimation based and the RSS profiling based techniques. The path loss exponent (PLE) is a key parameter in the distance estimation based localization algorithms, where distance is estimated from the RSS. The PLE measures the rate at which the RSS decreases with distance, and its value depends on the specific propagation environment. Existing techniques on PLE estimation rely on both RSS measurements and distance measurements in the same environment to calibrate the PLE. However, distance measurements can be difficult and expensive to obtain in some environments. In this paper we propose several techniques for online calibration of the PLE in wireless sensor networks without relying on distance measurements. We demonstrate that it is possible to estimate the PLE using only power measurements and the geometric constraints associated with planarity in a wireless sensor network. This may have a significant impact on distance-based wireless sensor network localization.
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Keywords: Computational geometry; Constraint theory; Multipath propagation; Routing algorithms; Sensor data fusion; Signal distortion; Cayley-Menger determinants; Geometric constraints; Path loss exponent (PLE); Received signal strength (RSS); Wireless sensor netwo Cayley-Menger determinant; Data fusion; Path loss exponent; Sensor network
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Source
Computer Networks
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Journal article
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2037-12-31
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